NOMA-enabled multi-beam satellite systems: Joint optimization to overcome offered-requested data mismatches
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
ProjectINTERFAZ RADIO PARA SISTEMAS HIBRIDOS TERRESTRE%2FSATELITE DE 5G Y FUTUROS (AEI-TEC2017-90093-C3-1-R)
Non-Orthogonal Multiple Access (NOMA) has the potentials to improve the performance of multi-beam satellite systems. The performance optimization in satellite-NOMA systems can be different from that in terrestrial-NOMA systems, e.g., considering distinctive channel models, performance metrics, power constraints, and limited flexibility in resource management. In this paper, we adopt a metric, Offered Capacity to requested Traffic Ratio (OCTR), to measure the requested-offered data (or rate) mismatch in multi-beam satellite systems. In the considered system, NOMA is applied to mitigate intra-beam interference while precoding is implemented to reduce inter-beam interference. We jointly optimize power, decoding orders, and terminal-timeslot assignment to improve the max-min fairness of OCTR. The problem is inherently difficult due to the presence of combinatorial and non-convex aspects. We first fix the terminal-timeslot assignment and develop an optimal fast-convergence algorithmic framework based on the Perron-Frobenius theory (PF) for the remaining joint power-allocation and decoding-order optimization problem. Under this framework, we propose a heuristic algorithm for the original problem, which iteratively updates the terminal-timeslot assignment and improves the overall OCTR performance. Numerical results verify that max-min OCTR is a suitable metric to address the mismatch issue, and is able to improve the fairness among terminals. On average, the proposed algorithm improves the max-min OCTR by 40.2% over Orthogonal Multiple Access (OMA).
CitationWang, A. [et al.]. NOMA-enabled multi-beam satellite systems: Joint optimization to overcome offered-requested data mismatches. "IEEE transactions on vehicular technology", Gener 2021, vol. 70, núm. 1, p. 900-913.